Application Control and Horizontal Scaling in Modern Cloud Middleware

Chapter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9570)

Abstract

This work is focused on a number of standard communication patterns of distributed system nodes via messages. Certain characteristics of modern practically applied communication systems are considered. The conclusions are based on the practical development of collective communication strategy processing services and the theoretical basis drawn in the course of testing a number of distributed system prototypes. Development trends of service oriented architecture in the field of interservice communications are considered, including the development tendencies of AMQP and ZMTP protocols.

Problems arising during the design and development of such systems from the horizontal scaling standpoint are specified. The problem of long term control is highlighted in the course of considering issues of data consistency between nodes, availability and partition tolerance. The process of changing workload distribution in a horizontally scaled system is described and issues of fault tolerance of the system in general and its nodes in particular are raised. A way of workload scaling by means of defining an evaluation criterion of node load determined by the system’s business logic and not by the characteristics of the communications level is offered. The efficiency of this approach is shown, with long term control systems used as an example.

Keywords

Cloud middleware Communication patterns Horizontal scaling Zeromq 

References

  1. 1.
    Degtyarev, A.B., Logvinenko, Y.: Agent system service for supporting river boats navigation. Procedia Comput. Sci. 1(1), 2717–2722 (2010)CrossRefGoogle Scholar
  2. 2.
    Bogdanov, A., Degtyarev, A., Nechaev, Y., Valdenberg, A.: Design of telemedicine system architecture. Healthc. IT Manage. 1(2), 31–33 (2006)Google Scholar
  3. 3.
    Bogdanov, A., Degtyarev, A., Nechaev, Y., Valdenberg, A.: Design of high-performance telemedicine system. Healthc. IT Manage. 1(1), 29–31 (2006)Google Scholar
  4. 4.
    Bogdanov, A.V., Degtyarev, A.B., Mareev, V., Nechaev, Y.: Flexible dynamic pooling of resources or service-oriented grid computing. Inf. Soc. 2, 61–70 (2012)Google Scholar
  5. 5.
    Gankevich, I., Gaiduchok, V., Gushchanskiy, D., Tipikin, Y., Korkhov, V., Degtyarev, A.B., Bogdanov, A.V., Zolotarev, V.: Virtual private supercomputer: Design and evaluation. In: Computer Science and Information Technologies (CSIT), IEEE, pp. 1–6 (2013)Google Scholar
  6. 6.
    Goedicke, M., Zdun, U.: A key technology evaluation case study: Applying a new middleware architecture on the enterprise scale. In: Emmerich, W., Tai, S. (eds.) EDO 2000. LNCS, vol. 1999, pp. 8–26. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  7. 7.
    Doddavula, S., Agrawal, I., Saxena, V.: Computer Communications and Networks. In: Mahmood, Z. (ed.) Cloud Computing. Cloud computing solution patterns: Infrastructural solutions, pp. 197–219. Springer, London (2013)CrossRefGoogle Scholar
  8. 8.
    Josuttis, N.: SOA in Practice. O’reilly, Sebastopol (2007)Google Scholar
  9. 9.
    Ghag, S.S., Bandopadhyaya, R.: Technical strategies and architectural patterns for migrating legacy systems to the cloud. In: Mahmood, Z., Saeed, S. (eds.) Software Engineering Frameworks for the Cloud Computing Paradigm. Computer Communications and Networks, pp. 235–254. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  10. 10.
    Huhns, M.N., Singh, M.P.: Service-oriented computing: Key concepts and principles. Int. Comput. IEEE 9(1), 75–81 (2005)CrossRefGoogle Scholar
  11. 11.
    Petcu, D., Rak, M.: Open-source cloudware support for the portability of applications using cloud infrastructure services. In: Mahmood, Z. (ed.) Cloud Computing. Computer Communications and Networks. Springer, Heidelberg (2013)Google Scholar
  12. 12.
    Yastrebov, I.: Rda3 high-level - api & architecture (2013). http://indico.cern.ch/getFile.py/access?contribId=3&resId=1&materialId=slides&confId=259755
  13. 13.
    Snyder, B., Bosnanac, D., Davies, R.: ActiveMQ in action. Manning (2011)Google Scholar
  14. 14.
    Videla, A., Williams, J.J.: RabbitMQ in action. Manning (2012)Google Scholar
  15. 15.
    Amazon, S.: Team, building scalable, reliable amazon ec2 applications with amazon sqs (2008). http://sqs-public-images.s3.amazonaws.com/Building_Scalabale_EC2_applications_with_SQS2.pdf
  16. 16.
  17. 17.
    Prinz, V., Fuchs, F., Ruppel, P., Gerdes, C., Southall, A.: Adaptive and fault-tolerant service composition in peer-to-peer systems. In: Meier, R., Terzis, S. (eds.) DAIS 2008. LNCS, vol. 5053, pp. 30–43. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  18. 18.
    Piël, N.: Zeromq an introduction. Retrieved 6(30), 2011 (2010)Google Scholar
  19. 19.
    Oudenstad, J., Rouvoy, R., Eliassen, F., Gjørven, E.: Brokering planning metadata in a P2P environment. In: Meier, R., Terzis, S. (eds.) DAIS 2008. LNCS, vol. 5053, pp. 168–181. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  20. 20.
    Schmid, M., Kroeger, R.: Decentralised QoS-management in service oriented architectures. In: Meier, R., Terzis, S. (eds.) DAIS 2008. LNCS, vol. 5053, pp. 44–57. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  21. 21.
    Wu, Q., Gu, Y.: Performance analysis and optimization of linear workflows in heterogeneous network environments. In: Preve, N.P. (ed.) Grid Computing. Computer Communications and Networks, pp. 89–120. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  22. 22.
    Dworak, A., Sobczak, M., Ehm, F., Sliwinski, W., Charrue, P.: Middleware trends and market leaders 2011. Technical report (2011)Google Scholar
  23. 23.
    Review of the controls middleware transport architecture and its use of zeromq (2013). http://indico.cern.ch/conferenceDisplay.py?confId=259755
  24. 24.
    Sliwinski, W.: Controls middleware renovation - technical overview (2013). http://indico.cern.ch/getFile.py/access?contribId=2&resId=1&materialId=slides&confId=259755
  25. 25.
  26. 26.
    Dworak, A., Ehm, F., Charrue, P., Sliwinski, W.: The new cern controls middleware. J. Phys.: Conf. Ser. 396, 012017 (2012). IOP PublishingGoogle Scholar
  27. 27.
    Vinoski, S.: Advanced message queuing protocol. Int. Comput. IEEE 10(6), 87–89 (2006)CrossRefGoogle Scholar
  28. 28.
  29. 29.
    Reitman, L., Ward, J., Wilber, J.: Service oriented architecture (soa) and specialized messaging patterns. A technical White Paper published by Adobe Corporation USA (2007)Google Scholar
  30. 30.
    Hintjens, P.: ZeroMQ: Messaging for Many Applications. O’Reilly (2013)Google Scholar
  31. 31.
    Brewer, E.A.: Towards robust distributed systems. In: PODC, vol. 7 (2000)Google Scholar
  32. 32.
    Pritchett, D.: Base: An acid alternative. Queue 6(3), 48–55 (2008)CrossRefGoogle Scholar
  33. 33.
    Focht, E., Jeutter, A.: AggMon: Scalable hierarchical cluster monitoring. In: Resch, M.M., Wang, X., Bez, W., Focht, E., Kobayashi, H. (eds.) Sustained Simulation Performance 2012, pp. 51–64. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  34. 34.
    Ivanović, D., Carro, M., Hermenegildo, M.: Constraint-based runtime prediction of SLA violations in service orchestrations. In: Kappel, G., Maamar, Z., Motahari-Nezhad, H.R. (eds.) Service Oriented Computing. LNCS, vol. 7084, pp. 62–76. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  35. 35.
    E. Duran, R., Zhang, L., Hayhurst, T.: Enabling GPU acceleration with messaging middleware. In: Abd Manaf, A., Sahibuddin, S., Ahmad, R., Mohd Daud, S., El-Qawasmeh, E. (eds.) ICIEIS 2011, Part III. CCIS, vol. 253, pp. 410–423. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  36. 36.
    Rao, J.S.: Optimization. In: Rao, J.S. (ed.) History of Rotating Machinery Dynamics. HMMS, vol. 20, pp. 341–351. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  37. 37.
    Iakushkin, O.: Intellectual scaling in a distributed cloud application architecture: A message classification algorithm. In: 2015 International Conference Stability and Control Processes in Memory of V.I. Zubov (SCP), pp. 634–637, October 2015Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Saint Petersburg State UniversitySt. PetersburgRussia

Personalised recommendations